Physical AI Engineering Consultant - Manager - Consulting - Open Location
EY · Memphis, TN · 3 wk ago
On-siteEngineering$143k–$262k/yrFull-time
About the role
Join our Artificial Intelligence and Data team to help bring solutions to our clients. As a Physical AI Engineering Consultant, you will work closely with clients and diverse teams from EY to create innovative AI solutions. You will be part of a dynamic and interdisciplinary team of scientists and engineers who love to tackle complex computational problems.
Responsibilities
- Research, build, and implement scalable artificial intelligence systems that learn and make predictions tailored to business requirements across various environments, including cloud and on-premises.
- Enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes.
- Monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions.
- Lead workstream delivery and ensure effective management of processes and projects.
- Manage professional employees and supervise teams to deliver complex technical initiatives, with accountability for performance and results.
- Engage actively with clients, participate in daily working sessions, and lead workstreams from planning through execution to closure.
- Identify opportunities for additional services and manage engagement economics.
Requirements
- A Bachelor’s degree required (4-year degree) focused on Business or Economics, Technology Entrepreneurship, Computer Science, Engineering, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning.
- Minimum of 5+ years of full-time working experience in Robotics, Digital Twin, and Computer Vision/Deep Learning/Reinforcement Learning.
- Proficiency in programming languages such as Python, C++, or Java, with experience in robotics frameworks (e.g., ROS) and simulation environments.
- Experience designing, building, and maintaining robotics systems and digital twin models.
- Hands-on experience with NVIDIA Omniverse or similar simulation environments for robotics and digital twin applications.
- Understanding of robotic systems, kinematics, dynamics, and control algorithms.
- Understanding of various sensors (e.g., LIDAR, cameras) and actuators used in robotic systems.
- Familiarity with creating and managing digital twins, including modeling, simulation, and real-time data integration.
- Knowledge of machine learning techniques and algorithms, particularly in the context of robotics and automation.
- Proficiency using data manipulation and analysis tools (Pandas, NumPy) to derive insights from sensor data and simulations, and experience with popular ML packages such as TensorFlow, PyTorch, or similar libraries.
- Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.
- A solid understanding of Machine Learning (ML) workflows including ingesting, analyzing, transforming data and evaluating results to make meaningful predictions.
- Experience with MLOps methods and platforms such as MLFlow.
- Experience with CI/CD practices to automate the testing and deployment of software in Software-in-the-loop (SIL) environments.
- Experience designing, building, and maintaining ML models, frameworks, and pipelines.
- Experience designing and deploying end-to-end ML workflows on at least one major cloud computing platform.
- A strong understanding of data structures, data modelling and software engineering best practices.
- Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
- Clearly communicate findings, recommendations, and opportunities to improve data systems and solutions.
- Experience with containerization and scaling models.
- Integrate models and feedback from downstream consumption systems - reporting and dashboards, AI driven applications.
- Experience with machine learning algorithms and data architecture design.
- A strong understanding of and/or interest in Agentic AI/Generative AI.
- Knowledge of sustainability practices in technology.
- Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
- Willingness to travel to meet client obligations.
Qualifications
- Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
- Strong judgment in selecting methods and techniques for obtaining results.
- Experience in managing client relationships and delivering high-quality service.
- Ability to lead teams effectively and manage change within the organization.
- Strong analytical and decision-making skills to guide project direction.
- Proven experience in project management and tracking deliverable completion.
- Ability to build and maintain relationships with clients and team members.
- Excellent communication skills to convey complex ideas effectively.
Skills and attributes for success
- Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
- Strong judgment in selecting methods and techniques for obtaining results.
- Experience in managing client relationships and delivering high-quality service.
- Ability to lead teams effectively and manage change within the organization.
- Strong analytical and decision-making skills to guide project direction.
- Proven experience in project management and tracking deliverable completion.
- Ability to build and maintain relationships with clients and team members.
- Excellent communication skills to convey complex ideas effectively.